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Ready. Checkpoint. GO.

Get a head start with the expanded Advanta IO Gene Expression Workflow.

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Gene expression profiling of the tumor microenvironment has proven effective in measuring immune response during research in cancer progression and therapeutic response. Preconfigured quantitative PCR (qPCR) panels containing hundreds of gene targets represent a potential solution, but can require significant time and resources to implement in the laboratory and can be difficult to customize for specific experimental needs.

The Advanta™ IO Gene Expression Assay workflow was designed to meet this need, detecting 170 gene expression markers involved in checkpoint therapeutic response. Ideal for accelerating the identification of potential predictive biomarker signatures of checkpoint immunotherapeutic response, the Advanta IO Gene Expression Assay was developed in collaboration with leading researchers from academia and biopharma to provide the right balance of biomarker breadth, assay flexibility and workflow efficiency.

As an expanded workflow solution, we now offer an optimized Advanta FFPE RNA Extraction Kit, which produces high-quality RNA from precious tumor samples and improves the sensitivity of tumor transcript detection. As an added benefit, a synthetic template representing the amplification targets of all 170 genes is also available as a positive control. When using this new kit and control together with the Advanta IO Gene Expression Assay on the Biomark™ HD system, researchers can accurately assess 24 to 96 tumor samples at a time with high confidence and efficiency.

Completing the workflow, the GO Immuno-Oncology Workbench was developed by GenomOncology to provide powerful, flexible and intuitive analysis of immuno-oncology datasets. Now available from Fluidigm, the GO Immuno-Oncology Workbench enables researchers to unlock new clinical insights from translational immuno-oncology studies, including the identification of meaningful gene expression biomarkers that correlate with therapeutic response.

“The GO Immuno-Oncology Workbench is a powerful software tool that enables comprehensive analysis of immuno-oncology cohorts, integrating molecular and phenotypic data together with immuno-oncology-specific annotations to power translational studies,” said Manuel Glynias, CEO of GenomOncology. “We are excited to see the new insights uncovered using this comprehensive approach, which we we offer in conjunction with Fluidigm to empower the growing immuno-oncology community.”

“Fluidigm is the partner of choice within the immuno-oncology research community, enabling deep interrogation of the tumor microenvironment and immune response with mass cytometry,” said Chris Linthwaite, President and CEO of Fluidigm. “In partnership with GenomOncology, we are expanding our immuno-oncology gene expression offering to the cancer community with a full microfluidics-based workflow solution from RNA extraction to data analysis. By providing a comprehensive view of tumor immunity, utilizing microfluidics and mass cytometry technologies, we are empowering researchers to uncover unique health insights that could transform the future of cancer care.”

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Deciphering T Cell Diversity in the Tumor Microenvironment

Evan Newell on decoding immune cell heterogeneity with mass cytometry

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Understanding the full complexity of the immune system and its response to infections and diseases, especially in cancer, has eluded researchers for decades. Whether analyzing blood or tissue samples, investigators have struggled to categorize the heterogeneity found in the T cell composition of different tumors.

In a recently published paper in Nature, Evan Newell, PhD, and colleagues identify a potential biomarker of tumor-antigen specificity and provide a new perspective on the heterogeneity of T cells in the tumor microenvironment. Newell led this research as a principal investigator at the Singapore Immunology Network (SIgN). First author Yannick Simoni, PhD, formally a senior research fellow at Singapore’s Agency for Science, Technology and Research (A*STAR), accumulated data for more than 140 different tumor samples from patients with lung and colorectal cancer to search for correlations between this heterogeneity and various characteristics of the patient samples.

“CyTOF technology has a really unique niche for interrogating the tumor microenvironment,” said Newell. “It has relatively high throughput and high dimensionality, allowing us to open up a lot of doors.”

Newell’s lab developed novel approaches for identifying and characterizing antigen-specific T cells. In this paper, his group used MHC tetramer staining in conjunction with mass cytometry for in-depth analysis of cellular phenotype and function.

His group and others “have been stuck on saying, ‘It’s crazy. There are so many different types of immune cells.’ And you can use all kinds of fancy analyses to show that it’s very diverse,” Newell said. “But we’ve taken it a little bit further by getting to some simple correlates of clinical states.”

Newell and his team used mass cytometry that relies on time-of-flight mass spectrometry (CyTOF® technology) to simultaneously assess antigen specificity and deep phenotypic characteristics of T cells. The resulting data shows that T cell populations infiltrating lung and colorectal tumors may be specific for tumor antigens or for a wide range of epitopes unrelated to cancer, such as viral antigens. Moreover, he discovered that these bystander T cells have diverse phenotypes that overlap with tumor-specific cells and lack CD39 expression.

CD39: A more accurate marker of tumor antigen specificity

Newell and Simoni’s discovery of a more accurate marker for tumor antigen specificity relied on a multiplexed approach that allowed them to simultaneously profile T cells within the tumor microenvironment for phenotype and function. Instead of focusing only on tumor-reactive cells, the team looked at all antigen-specific T cells and was able to identify cancer-unrelated antigen-specific T cells in tumors.

“We found a few examples of tumor-specific T cells, and then we also had examples of T cells specific for cancer-unrelated antigens, like the flu and Epstein-Barr virus. This was key in trying to interpret what all this heterogeneity meant,” Newell said.

The next step was to determine what was different about the non-cancer-specific T cells. Simoni observed that many of them expressed what typically have been identified as tumor-infiltrating T cell markers, such as CD69 and PD-1, which may have a role in tumor reactivity.

“The striking thing was that we saw hardly any expression of CD39, which is known as being immunosuppressive,” he said.

Since their findings showed that the tumor-specific T cells expressed CD39, Simoni could build a case for CD39 as a more accurate marker of tumor antigen specificity. Newell now believes CD39 also could be useful as a predictor of response to checkpoint blockade, and as a starting point for the development of novel therapeutics.

Advantage to using CyTOF technology for immune cell profiling

Newell started using mass cytometry for studying human T cell response as a postdoctoral student at Stanford University more than six years ago. He attributes much of his success to the technology’s ability to simultaneously look at many phenotypic markers and antigen specificity, allowing his team to better understand the number of distinct cellular phenotypes and how they are related to each other.

In the Nature paper described here, Newell also used whole transcriptome RNA-seq to validate his mass cytometry findings. He believes the two techniques make a powerful combination for identifying new markers associated with specific cell populations. However, Newell explains that compared to RNA-seq, mass cytometry “can more accurately measure protein and do it on a larger number of cells, which gives a much higher resolution when describing cellular heterogeneity.”

CyTOF applications beyond cancer research

Newell’s ultimate goal is to gain a better understanding of how the human immune system works, and he thinks the best way to accomplish this is by searching for co-variations.

“Mass cytometry is especially great for that because it’s really improving our understanding of immune system variation in humans,” Newell said. “It has also been excellent for mapping out trajectories of cellular development.”

In addition to providing cutting-edge technology platforms to researchers, SIgN aims to support Singapore biotechnology companies such as Newell’s spinoff immunoSCAPE, which provides antigen-specific T cell screening and profiling services. Newell, who established his lab at SIgN in 2012, has moved to the Fred Hutchinson Cancer Research Center in Seattle as part of the Vaccine and Infectious Disease Division. His lab will continue to investigate antigen-specific T cells in cancer and other diseases. He also has been working on developing computational approaches to improve analysis of these large datasets.

Beyond cancer research, Newell and colleagues are using mass cytometry to study a variety of topics from myeloid cell composition in dendritic cell development to T cell antigen specificity in viruses such as hepatitis B and dengue. By taking a multiplexed approach in investigating the phenotype and function of cells from different viral disease stages, Newell’s team can assess the use of T cell phenotypes as future biomarkers for patient outcomes.

“CyTOF technology has a really unique niche for interrogating the tumor microenvironment,” said Newell. “It has relatively high throughput and high dimensionality, allowing us to open up a lot of doors.”

Fluidigm Products are for Research Use Only. Not for use in diagnostic procedures.

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Quality RNA Means Better Cancer Research

Advanta IO Gene Expression Assay

Tumor gene expression profiling in cancer research is an effective tool for measuring immune response during cancer progression and treatment studies. As emerging therapies reveal new biomarkers and expand the need for sample testing, the costs and labor required to complete this important work also increase.

Cancer researchers now have a reliable, sensitive and cost-effective tool for identifying gene expression signatures from immune and cancer cells: The Advanta™ IO Gene Expression Assay is designed for use with the Biomark™ HD system. For optimized gene detection, pair it with the Advanta™ FFPE RNA Extraction Kit.

Improving the process

Processing FFPE samples can be challenging due to limited sample quantities or fragmented RNA transcripts caused by nucleic acid degradation as a result of tissue fixation and storage methods. In addition, most extraction kits rely on column purification to remove RNA and DNA, causing significant nucleic acid loss during the isolation process. To address this issue, the Advanta FFPE RNA Extraction Kit uses a column-free approach to effectively recover quality RNA from FFPE samples.

Download our product flyer to learn more about using the Advanta FFPE RNA Extraction Kit to accelerate your investigative research.

“Sirona Dx specializes in expression profiling of challenging FFPE samples and we welcomed the opportunity to partner with Fluidigm to develop an improved RNA extraction methodology. To date we have processed several hundred samples with the Advanta FFPE RNA Extraction Kit, and our pharma clients have been astonished by the quality of RNA extracted and delighted at our ability to interrogate more of their precious FFPE samples.”
—Nasry Yassa, CEO, Sirona Dx

Sirona Dx case study

Clinical research services provider Sirona Dx, Inc., based in Vancouver, Washington, performed gene expression analysis of FFPE samples extracted using the Advanta FFPE RNA Extraction Kit and a leading column-based commercial kit. After extraction, the group reverse-transcribed and preamplified the RNA and analyzed the cDNA on Biomark HD using the Advanta IO Gene Expression Assay panel containing 170 unique biomarkers for profiling tumor immunobiology and identification. Gene expression analysis data demonstrated more target gene detection in samples extracted using the Advanta FFPE RNA Extraction Kit. These samples typically showed lower cycle threshold values than those extracted using the alternative kit.

“Sirona Dx specializes in expression profiling of challenging FFPE samples and we welcomed the opportunity to partner with Fluidigm to develop an improved RNA extraction methodology,” said Sirona Dx CEO Nasry Yassa. “To date we have processed several hundred samples with the Advanta FFPE RNA Extraction Kit, and our pharma clients have been astonished by the quality of RNA extracted and delighted at our ability to interrogate more of their precious FFPE samples­.”

Contact us to learn more about the Advanta FFPE RNA Extraction Kit.

For Research Use Only. Not for use in diagnostic procedures.

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Mass Cytometry Webinar Series

Watch these webinars to learn how researchers are using mass cytometry applications

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Enabling multiparameter profiling of precious samples, mass cytometry has been instrumental in achieving new research breakthroughs in areas such as immunology, cancer immunotherapy, drug discovery, vaccine development and more around the world.

Watch the webinars below to learn how researchers are utilizing Helios™, a CyTOF system, and mass cytometry applications to further their research.

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Unlocking Topographic Biomarkers

The interactive histoCAT toolbox unifies the cytometry and imaging communities

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Embarking on the launch of a landmark technology designed to reveal unprecedented biological insights and improve the future of health care, we at Fluidigm are pleased to collaborate with scientists at the birthplace of Imaging Mass Cytometry™, the University of Zurich (UZH). Computational biologist Denis Schapiro of the Bodenmiller Lab talked with us about developing the data analysis software distributed with the Hyperion™ Imaging System. Here he shares what he’s learned in recent years as a pioneer in the emerging field of Imaging Mass Cytometry, and how the technology stands to impact life sciences by integrating cellular biology with molecular and spatial analysis.

Schapiro joined the Bodenmiller Lab to build a computational pipeline for Imaging Mass Cytometry, which was first featured in a published paper in the March 2014 issue of Nature Methods. He became the main developer of the histoCAT™ (histology topography cytometry analysis toolbox) software for analyzing highly multiplexed tissue data such as that produced by the Hyperion™ Imaging System, which relies on IMC™. The software has emerged as a key component of the technology.

In his August 2017 Nature Methodspaper on histoCAT design and application, Schapiro and co-first author Hartland Jackson demonstrated how they analyzed 49 breast cancer samples and identified cellular social networks associated with tumor grading. Researchers see different topographic structures in Grade 1 patients versus Grade 3. By quantifying patterns of interaction in the context of clinical outcomes, histoCAT could improve precision medicine applications across experimental cohorts for a range of diseases in the future. Doing so requires looking at both the composition of cell types and their spatial interactions.

“Now it’s possible to identify different cell types—potentially even all cell types—in a tissue and their exact location. You can then go beyond exploring which cell types are present in these tissues to ask questions about their signaling and functional states, and how the cells communicate.”
—Denis Schapiro, Bodenmiller Lab, University of Zurich

histoCAT workflow

Essentially, histoCAT combines imaging data with cytometry. The imaging community is trained to segment, annotate and analyze imaging data. It characterizes millions of cells using spatial features, but because of limited multiplexing capabilities has been unable to identity the cell lines or types in the tissue. In contrast, cytometry researchers have mastered single-cell analysis using scatter plots, tSNE (t-distributed stochastic neighbor embedding) visualizations and associated gating tools to investigate highly multiplexed CyTOF® datasets and identify cell types or phenotypes. But they have lacked spatial information.

Imaging Mass Cytometry multiplexing enables identification of many cell types in a tissue. “We know where the tumor cells and immune cells are located, and we know what cellular state they represent,” Schapiro said. “histoCAT unlocks this information so we can interactively select cells and ask questions about whether certain cell types and locations correlate with specific clinical information or outcomes. This could lead to the discovery of a new class of biomarkers: topographic biomarkers.”

“We designed histoCAT as a unique tool for combining cellular phenotypes with spatial information,” Schapiro said. “You can identify individual cells of interest on a scatter plot and visualize them directly in their spatial context. Alternatively, it’s possible to select cells or structures in their spatial context and visualize those in scatter plots and other single-cell visualizations. We call this interactive workflow between cytometry and image analysis the round-trip.

“Additionally, you can capture the tissue architecture quantitatively through permutation testing to see how the structure differs from a random cell type distribution,” he said, offering examples of using histoCAT in the context of immune infiltration and stroma-to-tumor interactions.

He offered this advice to new users: “Imaging Mass Cytometry is the right tool if you have a heterogeneous system with a lot of hidden spatial information. With histoCAT and other open source tools, you can do preliminary analysis leading to exciting results. With the right question, you can then follow up with more advanced tools and computational collaborations.”

histoCAT applications

Schapiro expects histoCAT to benefit scientists exploring a range of health and disease applications including histology, digital pathology and translational research. The capability of IMC to measure abundant information on a single cell with spatial resolution makes it possible to identify patterns in immuno-oncology and diseases on a single rather than consecutive sections. “The amazing part of developing histoCAT is that people can use it to do things I haven’t even thought of yet.”

He described how IMC and histoCAT support his own research: “What I value most about the Hyperion Imaging System technology is getting multiplexed spatial measurements. Now it’s possible to identify different cell types—potentially even all cell types—in a tissue, and their exact location. You can then go beyond exploring which cell types are present in these tissues to ask questions about their signaling and functional states and how these cells communicate.”

He plans to extend the methods he helped develop for dozens of samples to analyze hundreds or even thousands of samples for even deeper clinical research insights. He’s enthusiastic about optimizing the data analysis pipeline to answer questions such as how to analyze data efficiently with thousands or even 100,000 samples, and how to learn from this data. How do we normalize and segment the data and correct for errors? “I’m excited to focus on this cutting-edge technology,” he said. “We need to step-by-step continue to improve it, and then work with the broader community to make it even better.”

Developing histoCAT represents a significant step in advancing the potential of mass cytometry to deeply interrogate tissue samples. “That is the dream: histoCAT combines the immune system knowledge of the cytometry community with the pattern knowledge of pathologists and histologists, all in one software,” Schapiro said. “This is growing into a great community with so many new ideas. There will be lots of possibilities for collaborations.”

Supported by the Swiss National Science Foundation and a UZH BioEntrepreneur-Fellowship, Schapiro continues to work on multiplexed imaging data analysis as an Independent fellow affiliated with Harvard Medical School and the Broad Institute at MIT and Harvard. “The next step is to combine single-cell multiplexed imaging with single-cell transcriptomics.”

For news and updates and to learn more about how the Hyperion Imaging System can advance your research and reveal insights about cancer and other areas of health and disease research, send us your contact information below.

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Striking Balance in Throughput and Resolution

Christophe Lancrin on revealing new transcription factors using C1 and Biomark

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Biomark HD vs. bulk analysis

Christophe Lancrin uses C1™ at EMBL and has also compared Biomark™ HD expression data to bulk analysis for backup confirmation. His verdict: “C1 and Biomark are really good products, ideal for robust and sensitive detection of genes at the single-cell level. We get excellent results with them.”

Christophe Lancrin, PhD, leads a Research Group at the European Molecular Biology Laboratory (EMBL) in Rome, Italy. He recently spoke with Fluidigm about his 2018 eLife paper, “Single-cell transcriptomics reveals a new dynamical function of transcription factors during embryonic hematopoiesis,”describing how he used C1™ and Biomark™ HD to identify an intermediate cell population between endothelial and blood cells during endothelial to hematopoietic transition (EHT). In the publication, he also discusses using C1 for full-length mRNA sequencing to identify a new gene regulatory network involving seven key transcription factors.

His research group at EMBL explores cell fate decisions and how endothelial cells grow blood progenitors and stem cells during embryonic development. Understanding EHT depends on identifying essential genetic regulatory mechanisms involved in the biological process. For this study, he and first author Dr. Isabelle Bergiers, PhD, set out to reveal the gene regulatory network responsible for switching off the endothelial cell fate and switching on the blood program and generating blood stem cells.

Recognizing that ultrahigh-throughput 3ʹ end RNA sequencing may be insufficient for detecting low abundant transcripts such as those coding for transcription factors, Dr. Lancrin launched his study with a hypothesis: Using targeted gene expression as a starting point, genomicists can apply highly sensitive single-cell real-time PCR technology to gain valuable insights for investigations into health and disease research.

Starting with 95 target genes associated with hematopoietic, endothelial and vascular smooth muscle cells, the team isolated embryonic endothelial cells for targeted gene expression using the Biomark HD system and assessed the expression patterns by single-cell real-time PCR to understand the process of EHT. Dr. Lancrin’s group discovered a population with endothelial and hematopoietic characteristics co-expressing seven essential transcription factors at the single-cell level.

In the eLife paper, the authors make a strong case for hypothesis-driven low-throughput single-cell sequencing employing highly sensitive full-length transcriptome analysis with the C1 platform, noting that sequencing 192 single cells was enough to reveal a new gene regulatory network involving the Runx1, Gata2, Tal1, Fli1, Lyl1, Erg and Lmo2 transcription factors. This finding did not require ultrahigh-throughput RNA sequencing analysis.

“Single-cell analysis is powerful. When you work in bulk, you miss information. Working with single cells is definitely a big plus but you need to use the right technology for the right question.” —Christophe Lancrin, PhD, EMBL

A summary of the study

The investigators produced data suggesting that even though the proto-oncogene-encoded protein Fli1 (transcription factor Friend leukemia integration 1) initially supports the endothelial cell fate, it acquires a prohematopoietic role when co-expressed with protein Runx1 (runt-related transcription factor 1).

Bergiers et al. concluded that “this work demonstrates the power of single-cell RNA sequencing for characterizing complex transcription factor dynamics.” The eLife paper notes that “although bulk transcriptomics can reveal crucial overall gene correlations between semi-stable cellular states, it cannot resolve subtler gene interactions occurring in complex transitional states. In addition, using a bulk approach makes it difficult to infer the direct consequences on the transcriptional landscape upon which these TFs are acting. These limitations can be overcome by the use of single-cell approaches.”

While stem cells are responsible for an organism’s development of specialized cell types, understanding how they form is necessary for assimilating cellular development and regenerative medicine applications. A vital function of many species, EHT is the embryonic process wherein vascular endothelial cells develop into blood stem cells.

When Dr. Lancrin and the researchers used Biomark with the classical endothelial genes and hematopoietic genes, they realized there were three different populations in the embryonic endothelium: endothelial, hematopoietic and one in between the two. Finding dual identity in both endothelial and hematopoietic genes, they identified a cell type in transition between the two stages. Looking closely, they discovered the seven transcription factors co-expressing both endothelial and hematopoietic genes were the only population expressing them all at single-cell resolution.

To clarify the findings, the team asked whether the genetic expression was a consequence or a cause of this dual identity. Using the embryonic stem cell (ESC) differentiation model into blood cells, they created an ESC line where all these factors could be over-expressed simultaneously at the single-cell level. Using this tool, they discovered that the co-expression of these transcription factors was in fact responsible for the dual endothelial and hematopoietic identity.

After proving their hypothesis, the EMBL scientists used C1 to identify genes linking to those transcription factors, to find certain targets for them. They discovered GPR-56 to be one of the target genes. There was an increase in the expression of this gene, which happens to be involved in hematopoiesis. The Lancrin group was surprised to learn that GPR-56 expression could not explain the dual endothelial and hematopoietic identity.

“Strikingly, we saw there were two transition factors linked to the same genes but in opposite relationships,” he said. “This suggested that some transcription factors were working against each other. We proved that this was not just correlation; it was actually the cause of the dual endothelial and hematopoietic identity.”

By modifying the relative quantity of these transcription factors, the Lancrin group eventually demonstrated that these factors were in a competition, which was responsible for the dual identity. “The competition is basically between two groups of transcription factors,” he said, “one supporting the blood cell fate and the other the endothelial identity.”

For this study, the investigators needed the C1 full-length mRNA sequencing technology because of its sensitivity. Dr. Lancrin explained, “We not only needed to detect transcription factors, we had to detect a range of gene expression levels. We required higher-quality sequencing data to perform these challenging analyses.”

Potential personalized medicine implications

The EMBL group realized that the Fli1 transcription factor supporting the endothelial cell fate essentially switches activity at some point during the EHT transition. Fli1 initially supports the endothelial cell fate but following expression of Runx1—master regulator of blood cell development—Fli1 starts to support the formation of blood cells. a football analogy, Dr. Lancrin likened it to two equal teams competing against each other. If suddenly a number of players switch sides, then one team must win, and it will be the team with more players. That study was the first to provide clear insights for him. “What we found could potentially help researchers to produce blood cells more efficiently, potentially by using small molecules affecting the interaction between Fli1 and Runx1.”

Dr. Lancrin plans to continue doing single-cell transcription analysis for more investigations, such as identifying what other aspects of transcription factor activity can be regulated. The eLife paper makes it clear that despite the small number of cells, his research was impactful because of how the scientists set up and modeled the study. “Single-cell analysis is powerful,” he said. “When you work in bulk, you miss information. Working with single cells is definitely a big plus but you need to use the right technology for the right question.”

Future applications

Generating embryonic stem cell-like(ESC-like) induced pluripotent stem cells (iPSCs) from fully-differentiated cell types such as skin fibroblasts was a breakthrough in regenerative medicine. Important work remains to be done to efficiently differentiate iPSC or ESC for specific blood cell progenitors like hematopoietic stem cells (HSCs), so Dr. Lancrin is focusing his research on revealing the mechanisms underlying HSC formation from endothelial cells. “Combining single-cell transcriptomics, computational biology, time-lapse microscopy and loss and gain of function experiments in vitro and in vivo, we plan to identify signaling pathways and transcriptional regulators involved in generating hematopoietic stem and progenitor cells during embryonic life,” he said. If all goes as planned, his research will lead to the development of new strategies to improve methods of blood cell generation from ESC or iPSC for regenerative medicine.

Dr. Lancrin believes his findings could potentially help researchers design more efficient approaches to generate blood cells from ESCs or iPSCs by influencing key transcription factor activity. Looking beyond hematopoiesis, investigators could apply the single-cell transcriptomics approaches from this study to gain insights about different cellular transitions such as the epithelial to mesenchymal transition occurring during development and in disease states such as cancer metastasis.

“Our computational approach for the study of transcription factor interaction will help to understand the formation of HSCs from endothelial cells,” he said.

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7th Annual Mass Cytometry Summit Recap

Friday, April 27, 2018 | Prague

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Get the Abstracts

On April 27, 2018, the mass cytometry community gathered in Prague at the 7th Annual Mass Cytometry Summit to share knowledge, network with colleagues and forge collaborations to further our understanding of the biological bases for health and disease.

Drawing over 200 attendees from around the world, the Summit had an information-rich agenda that included over a dozen scientific presentations and an engaging panel discussion by leading scientists.

Topics included workflow best practices, data analysis methods, new applications and research insights uncovered using mass cytometry and Imaging Mass Cytometry™.

"Some of the best cytometry at CYTO." — Assistant professor, Summit attendee

“I am inspired by the ways people have used mass cytometry and data analysis. I can see ways to incorporate these ideas in my own research and the research of others who use my facility.” — Joseph Slupsky, Department of Molecular and Clinical Cancer Medicine, University of Liverpool

“Well-organized. Great mix of speakers.” — Sylvia Lui, Manchester Collaborative Centre for Inflammation Research (MCCIR), University of Manchester

“No-brainer. I learn something every year. If you are performing mass cytometry, you need to be here.” — Evan Jellison, Director Flow Cytometry, University of Connecticut Health Center

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Bringing Immuno-Oncology into Focus

Advanta IO Gene Expression Assay and Workflow

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The Biomark HD advantage

The flexible Biomark HD system provides scalable performance to meet the complex needs of the molecular research laboratory. Achieve new economies of scale across multiple applications, all on the same system:

Reveal the molecular signatures of tumor immune response

Tumor gene expression has proven effective in measuring immune response during cancer progression and therapeutic response. As emerging therapies reveal new biomarkers and expand the need for samples, the costs and labor required to complete this important work also rise. Cancer researchers now have a reliable, sensitive and cost-effective toolset for identifying gene expression signatures from immune and cancer cells: the Advanta™ IO Gene Expression Assay, used with the Biomark™ HD system.

A powerful immuno-oncology focused assay

The Advanta IO Gene Expression Assay was developed in collaboration with leading researchers in the biopharmaceutical industry to provide the right balance of biomarker breadth, assay flexibility and workflow efficiency.

The panel consists of 170 genes, including 91 reported in Nature, where Roy Herbst et al. defined a gene set representing tumor and immune response. The panel includes markers for:

Immune cell identification

Immune and cancer cell function

Immune regulation and cell fate

Checkpoint therapy response

Optimized for FFPE and fresh frozen tumor samples, the Advanta IO Gene Expression Assay uses TaqMan® chemistry to sensitively measure gene expression, with five reference genes serving as analysis controls. Combined with Fluidigm microfluidics technology, the assay uniquely offers significant workflow efficiencies over traditional gene expression profiling methods. Each reaction is miniaturized to nanoliter volume and controlled using precise automation to empower accurate and cost-effective qPCR analysis across a large dynamic range. Since assay introduction into the integrated fluidic circuit (IFC) is under user control, researchers also have the flexibility to add up to 17 new assays or exchange gene assays within the panel to achieve experimental goals—all without affecting the original panel content, protocol or workflow.

DOWNLOAD THE FLYER to learn more about the Advanta IO Gene Expression Assay workflow using the Biomark HD system, and to see the list of gene expression targets covered in the assay.

Sample case study

In a 2016 paper published by The Lancet for the POPLAR study, “Atezolizumab versus docetaxel for patients with previously treated non-small-cell lung cancer,” Louis Fehrenbacher et al. detailed how they “assessed efficacy and safety of atezolizumab versus docetaxel in previously treated NSCLC, analyzed by PD-L1 expression levels on tumor cells and tumor-infiltrating immune cells and in the intention-to-treat population.” The team showed that “patients with pre-existing immunity, defined by high T-effector–interferon-γ-associated gene expression, had improved overall survival with atezolizumab.”

Fehrenbacher’s group noted that atezolizumab “significantly improved survival compared with docetaxel in patients with previously treated NSCLC. Improvement correlated with PD-L1 immunohistochemistry expression on tumor cells and tumor-infiltrating immune cells,” leading them to conclude: “PD-L1 expression is predictive for atezolizumab benefit. Atezolizumab was well tolerated, with a safety profile distinct from chemotherapy.”

The researchers performed the clinical trial using immunohistochemistry, and also ran a gene expression panel of 91 genes featured in the Herbst paper. These genes are included in the Advanta IO Gene Expression Assay. The team subsequently used these results to develop a gene signature based on a subset of the panel, effectively predicting therapeutic response that provides data that could potentially be used for developing future diagnostics tests.

Achieve greater overall productivity

The Advanta IO Gene Expression Assay is optimized to run on the powerful and flexible Biomark HD system. This automated system enables researchers to easily run from 24 to 96 samples at once with limited hands-on time, while delivering trusted performance. Together with the capability to sensitively detect biomarkers across defined T cell subsets, immune regulation, immune cell fate, cytokines, chemokines and more with exceptional cost-efficiency, this assay offers an ideal solution to meet the rigorous demands of translational research studies.

Ordering Information

Each assay kit contains reagents and assays for preamplification and gene expression, along with IFCs and Control Line Fluid. Assays for the 24.192 IFC are provided in dried-down form. Assays for the 96.96 IFC are provided in liquid form.

Seminar | Advancing Translational and Clinical Research

Hear Dr. Akil Merchant, MD, describe how research teams from the University of Southern California use Imaging Mass Cytometry™ to assess circulating tumor cells in the blood and analyze immune cells within the tumor microenvironment.

In this recorded live seminar, Merchant discusses:

how Imaging Mass Cytometry was integrated with the HD-SCA assay to study the role of CTCs in prostate and breast cancer

the simultaneous analysis of multiple markers to identify TREG cells within the tumor microenvironment

the characterization of immune infiltrate in Hodgkin’s lymphoma

Researchers in Merchant’s lab are investigating how tumor cells interact with their microenvironment and how this interaction contributes to the development and maintenance of cancer. They are studying how immune cells are trafficked into the tumor space and how immune cells can be harnessed to treat cancer. They are also interested in signaling pathways in cancer cells that confer resistance to chemotherapy. Merchant is a practicing hematologist and oncologist at USC Norris Comprehensive Cancer Center. He also participates in several clinical trials for patients with various cancers.

Akil Merchant, MDAssistant Professor of Medicine
Keck School of Medicine
University of Southern California